Head-related transfer function

ABSTRACT

Example systems, devices, media, and methods are described for efficiently processing an audio track of a virtual object with a head-related transfer function (HRTF). Audio tracks are processed by determining a current position (direction and optionally distance) of the virtual object with respect to the head of a user, identifying a current audio zone from predefined audio zones responsive to the determined current position where each of the audio zones has a corresponding left predefined filter and a corresponding right predefined filter, applying the left and the right predefined filters corresponding to the current audio zone to the audio track to produce a left audio signal and a right audio signal, and presenting the left audio signal with a first speaker and the right audio signal with a second speaker.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional application Ser.No. 17/110,424 filed on Dec. 3, 2020, the contents of which areincorporated fully herein by reference.

TECHNICAL FIELD

Examples set forth in the present disclosure relate to the field ofaudio signal processing. More particularly, but not by way oflimitation, the present disclosure describes head-related transferfunction models for efficiently processing audio signals correspondingto virtual objects.

BACKGROUND

A head-related transfer function (HRTF) is a response that characterizeshow an ear of a user receives a sound from a point in space. As soundstrikes the user, the size and shape of the head, ears, ear canal, thedensity of the head, and the size and shape of nasal and oral cavities,transform the sound and affect how it is perceived by boosting somefrequencies and attenuating others.

A pair of HRTFs, one for each ear, can be used to synthesize a binauralsound that seems to come from a particular point in space. Each transferfunction describes how a sound from a specific point will arrive at arespective ear (e.g., at the outer end of the auditory canal).

BRIEF DESCRIPTION OF THE DRAWINGS

Features of the various examples described will be readily understoodfrom the following detailed description, in which reference is made tothe figures. A reference numeral is used with each element in thedescription and throughout the several views of the drawing. When aplurality of similar elements is present, a single reference numeral maybe assigned to like elements, with an added lower-case letter referringto a specific element.

The various elements shown in the figures are not drawn to scale unlessotherwise indicated. The dimensions of the various elements may beenlarged or reduced in the interest of clarity. The several figuresdepict one or more implementations and are presented by way of exampleonly and should not be construed as limiting. Included in the drawingare the following figures:

FIG. 1A is a side view (right) of an example hardware configuration ofan eyewear device suitable for use in an HRTF modeling system;

FIG. 1B is a perspective, partly sectional view of a right corner of theeyewear device of FIG. 1A depicting a right visible-light camera, and acircuit board;

FIG. 1C is a side view (left) of an example hardware configuration ofthe eyewear device of FIG. 1A, which shows a left visible-light camera;

FIG. 1D is a perspective, partly sectional view of a left corner of theeyewear device of FIG. 1C depicting the left visible-light camera, and acircuit board;

FIGS. 2A and 2B are rear views of example hardware configurations of aneyewear device utilized in the HRTF modeling system;

FIG. 3 is a diagrammatic depiction of a three-dimensional scene, a leftraw image captured by a left visible-light camera, and a right raw imagecaptured by a right visible-light camera;

FIG. 4 is a functional block diagram of an example HRTF modeling systemincluding a wearable device (e.g., an eyewear device) and a serversystem connected via various networks;

FIG. 5 is a diagrammatic representation of an example hardwareconfiguration for a mobile device of the HRTF modeling system of FIG. 4;

FIG. 6 is a schematic illustration of a user in an example environmentfor use in describing simultaneous localization and mapping;

FIG. 7 is a flow chart listing steps in an example method of displayingvirtual objects in a physical environment;

FIG. 8A is an illustration of virtual objects in audio zones surroundinga head of a user in a head-related transfer function (HRTF) model;

FIG. 8B is a graphical user interface for use in testing predefinedfilters of the head-related transfer function model of FIG. 8A;

FIG. 9A is a flow chart listing the steps in an example method ofprocessing an audio track of a virtual object using a head in accordancewith the HRTF of FIG. 8A;

FIG. 9B is a flow chart listing steps in an example method of processingan audio track to add directional velocity information;

FIG. 9C is a flow chart listing steps in an example method of processingan audio track to add depth information; and

FIG. 10 is a perspective illustration of a virtual objects presented ona display of an eyewear device.

DETAILED DESCRIPTION

Various implementations and details are described with reference toexamples, including systems and methods implementing a head-relatedtransfer function (HRTF) model. The HRTF models described herein breakdown the space surrounding the user (also referred to herein aslistener) into 36 zones, each with a fixed set of predetermined filters(e.g., biquad filters) requiring fewer calculations than conventionalHRTF models. As a sound object moves from zone to zone, the new zone'spre-determined filters are applied. This results in a complexityreduction of approximately 2 orders of magnitude over conventionaltechniques, thereby decreasing the overall computational load for theHRTF model and allowing for more simultaneous objects to be calculatedand transformed.

In contrast, conventional HRTF modeling requires capturing the currentposition of any sound using multiple fast Fourier transforms (FFTs) togenerate the HRTF, and then long-tail (e.g., 256 or more sample) finiteimpulse response filters (FIRs) to implement. Such conventionaltechniques are computationally expensive.

The following detailed description includes systems, methods,techniques, instruction sequences, and computing machine programproducts illustrative of examples set forth in the disclosure. Numerousdetails and examples are included for the purpose of providing athorough understanding of the disclosed subject matter and its relevantteachings. Those skilled in the relevant art, however, may understandhow to apply the relevant teachings without such details. Aspects of thedisclosed subject matter are not limited to the specific devices,systems, and method described because the relevant teachings can beapplied or practice in a variety of ways. The terminology andnomenclature used herein is for the purpose of describing particularaspects only and is not intended to be limiting. In general, well-knowninstruction instances, protocols, structures, and techniques are notnecessarily shown in detail.

The terms “coupled” or “connected” as used herein refer to any logical,optical, physical, or electrical connection, including a link or thelike by which the electrical or magnetic signals produced or supplied byone system element are imparted to another coupled or connected systemelement. Unless described otherwise, coupled or connected elements ordevices are not necessarily directly connected to one another and may beseparated by intermediate components, elements, or communication media,one or more of which may modify, manipulate, or carry the electricalsignals. The term “on” means directly supported by an element orindirectly supported by the element through another element that isintegrated into or supported by the element.

The term “proximal” is used to describe an item or part of an item thatis situated near, adjacent, or next to an object or person; or that iscloser relative to other parts of the item, which may be described as“distal.” For example, the end of an item nearest an object may bereferred to as the proximal end, whereas the generally opposing end maybe referred to as the distal end.

The orientations of the eyewear device, other mobile devices, associatedcomponents and any other devices incorporating a camera, an inertialmeasurement unit, or both such as shown in any of the drawings, aregiven by way of example only, for illustration and discussion purposes.In operation, the eyewear device may be oriented in any other directionsuitable to the particular application of the eyewear device; forexample, up, down, sideways, or any other orientation. Also, to theextent used herein, any directional term, such as front, rear, inward,outward, toward, left, right, lateral, longitudinal, up, down, upper,lower, top, bottom, side, horizontal, vertical, and diagonal are used byway of example only, and are not limiting as to the direction ororientation of any camera or inertial measurement unit as constructed oras otherwise described herein.

Advanced augmented reality (AR) technologies, such as computer visionand object tracking, may be used to produce a perceptually enriched andimmersive experience. Computer vision algorithms extractthree-dimensional data about the physical world from the data capturedin digital images or video. Object recognition and tracking algorithmsare used to detect an object in a digital image or video, estimate itsorientation or pose (e.g., six degrees of freedom; x, y, z, pitch, yaw,roll), and track its movement over time.

The term “pose” refers to the static position and orientation of anobject at a particular instant in time. The term “gesture” refers to theactive movement of an object, such as a hand, through a series of poses,sometimes to convey a signal or idea. The terms, pose and gesture, aresometimes used interchangeably in the field of computer vision andaugmented reality. As used herein, the terms “pose” or “gesture” (orvariations thereof) are intended to be inclusive of both poses andgestures; in other words, the use of one term does not exclude theother.

Additional objects, advantages and novel features of the examples willbe set forth in part in the following description, and in part willbecome apparent to those skilled in the art upon examination of thefollowing and the accompanying drawings or may be learned by productionor operation of the examples. The objects and advantages of the presentsubject matter may be realized and attained by means of themethodologies, instrumentalities and combinations particularly pointedout in the appended claims.

Reference now is made in detail to the examples illustrated in theaccompanying drawings and discussed below.

FIG. 1A is a side view (right) of an example hardware configuration ofan eyewear device 100 which includes a touch-sensitive input device ortouchpad 181. As shown, the touchpad 181 may have a boundary that issubtle and not easily seen; alternatively, the boundary may be plainlyvisible or include a raised or otherwise tactile edge that providesfeedback to the user about the location and boundary of the touchpad181. In other implementations, the eyewear device 100 may include atouchpad on the left side instead of or in addition to touchpad 181.

The surface of the touchpad 181 is configured to detect finger touches,taps, and gestures (e.g., moving touches) for use with a GUI displayedby the eyewear device, on an image display, to allow the user tonavigate through and select menu options in an intuitive manner, whichenhances and simplifies the user experience.

Detection of finger inputs on the touchpad 181 can enable severalfunctions. For example, touching anywhere on the touchpad 181 may causethe GUI to display or highlight an item on the image display, which maybe projected onto at least one of the optical assemblies 180A, 180B.Double tapping on the touchpad 181 may select an item or icon. Slidingor swiping a finger in a particular direction (e.g., from front to back,back to front, up to down, or down to) may cause the items or icons toslide or scroll in a particular direction; for example, to move to anext item, icon, video, image, page, or slide. Sliding the finger inanother direction may slide or scroll in the opposite direction; forexample, to move to a previous item, icon, video, image, page, or slide.The touchpad 181 can be virtually anywhere on the eyewear device 100.

In one example, an identified finger gesture of a single tap on thetouchpad 181, initiates selection or pressing of a GUI element in theimage presented on the image display of the optical assembly 180A, 180B.An adjustment to the image presented on the image display of the opticalassembly 180A, 180B based on the identified finger gesture can be aprimary action which selects or submits the GUI element on the imagedisplay of the optical assembly 180A, 180B for further display orexecution.

As shown, the eyewear device 100 includes a right visible-light camera114B. As further described herein, two cameras 114A, 114B capture imageinformation for a scene from two separate viewpoints. The two capturedimages may be used to project a three-dimensional display onto an imagedisplay for viewing with three-dimensional (3D) glasses or the displaysof augmented reality or virtual reality eyewear devices.

The eyewear device 100 includes a right optical assembly 180B with animage display to present images, such as depth images. As shown in FIGS.1A and 1B, the eyewear device 100 includes the right visible-lightcamera 114B. The eyewear device 100 can include multiple visible-lightcameras 114A, 114B that form a passive type of three-dimensional camera,such as a stereo camera, of which the right visible-light camera 114B islocated on a right corner 110B. As shown in FIGS. 1C-D, the eyeweardevice 100 also includes a left visible-light camera 114A.

Left and right visible-light cameras 114A, 114B are sensitive to thevisible-light range wavelength. Each of the visible-light cameras 114A,114B have a different frontward facing field of view which areoverlapping to enable generation of three-dimensional depth images, forexample, right visible-light camera 114B depicts a right field of view111B. Generally, a “field of view” is the part of the scene that isvisible through the camera at a particular position and orientation inspace. The fields of view 111A and 111B have an overlapping field ofview 304 (FIG. 3 ). Objects or object features outside the field of view111A, 111B when the visible-light camera captures the image are notrecorded in a raw image (e.g., photograph or picture). The field of viewdescribes an angle range or extent, which the image sensor of thevisible-light camera 114A, 114B picks up electromagnetic radiation of agiven scene in a captured image of the given scene. Field of view can beexpressed as the angular size of the view cone; i.e., an angle of view.The angle of view can be measured horizontally, vertically, ordiagonally.

In an example configuration, one or both visible-light cameras 114A,114B has a field of view of 100° and a resolution of 480×480 pixels. The“angle of coverage” describes the angle range that a lens ofvisible-light cameras 114A, 114B or infrared camera 410 (see FIG. 4 )can effectively image. Typically, the camera lens produces an imagecircle that is large enough to cover the film or sensor of the cameracompletely, possibly including some vignetting (e.g., a darkening of theimage toward the edges when compared to the center). If the angle ofcoverage of the camera lens does not fill the sensor, the image circlewill be visible, typically with strong vignetting toward the edge, andthe effective angle of view will be limited to the angle of coverage.

Examples of such visible-light cameras 114A, 114B include ahigh-resolution complementary metal-oxide-semiconductor (CMOS) imagesensor and a digital VGA camera (video graphics array) capable ofresolutions of 480p (e.g., 640×480 pixels), 720p, 1080p, or greater.Other examples include visible-light cameras 114A, 114B that can capturehigh-definition (HD) video at a high frame rate (e.g., thirty to sixtyframes per second, or more) and store the recording at a resolution of1216 by 1216 pixels (or greater).

The eyewear device 100 may capture image sensor data from thevisible-light cameras 114A, 114B along with geolocation data, digitizedby an image processor, for storage in a memory. The visible-lightcameras 114A, 114B capture respective left and right raw images in thetwo-dimensional space domain that comprise a matrix of pixels on atwo-dimensional coordinate system that includes an X-axis for horizontalposition and a Y-axis for vertical position. Each pixel includes a colorattribute value (e.g., a red pixel light value, a green pixel lightvalue, or a blue pixel light value); and a position attribute (e.g., anX-axis coordinate and a Y-axis coordinate).

In order to capture stereo images for later display as athree-dimensional projection, the image processor 412 (shown in FIG. 4 )may be coupled to the visible-light cameras 114A, 114B to receive andstore the visual image information. The image processor 412, or anotherprocessor, controls operation of the visible-light cameras 114A, 114B toact as a stereo camera simulating human binocular vision and may add atimestamp to each image. The timestamp on each pair of images allowsdisplay of the images together as part of a three-dimensionalprojection. Three-dimensional projections produce an immersive,life-like experience that is desirable in a variety of contexts,including virtual reality (VR) and video gaming.

The eyewear device 100 additionally has a stereo speaker systemincluding a left speaker 185A for presenting audio signals to a left earof wearer and a right speaker 185B for presenting audio signals to aright ear of the wearer. An audio processor 413 (FIG. 4 ) of the stereospeaker system delivers audio signals to the left speaker 185A and theright speaker 185B.

FIG. 1B is a perspective, cross-sectional view of a right corner 110B ofthe eyewear device 100 of FIG. 1A depicting the right visible-lightcamera 114B of the camera system, and a circuit board 140B. FIG. 1C is aside view (left) of an example hardware configuration of an eyeweardevice 100 of FIG. 1A, which shows a left visible-light camera 114A ofthe camera system. FIG. 1D is a perspective, cross-sectional view of aleft corner 110A of the eyewear device of FIG. 1C depicting the leftvisible-light camera 114A of the camera system, and a circuit board140A.

Construction and placement of the left visible-light camera 114A issubstantially similar to the right visible-light camera 114B, except theconnections and coupling are on the left lateral side 170A rather thanthe right lateral side 170B. As shown in the example of FIG. 1B, theeyewear device 100 includes the right visible-light camera 114B and aright circuit board 140B, which may be a flexible printed circuit board(PCB). A right hinge 126B connects the right corner 110B to a righttemple 125B of the eyewear device 100. In some examples, components ofthe right visible-light camera 114B, the flexible PCB 140B, or otherelectrical connectors or contacts may be located on the right temple125B or the right hinge 126B. A left hinge 126A connects the left corner110A to a left temple 125A of the eyewear device 100. In some examples,components of the left visible-light camera 114A, the flexible PCB 140A,or other electrical connectors or contacts may be located on the lefttemple 125A or the left hinge 126A.

The right corner 110B includes corner body 190 and a corner cap, withthe corner cap omitted in the cross-section of FIG. 1B. Disposed insidethe right corner 110B are various interconnected circuit boards, such asPCBs or flexible PCBs, that include controller circuits for rightvisible-light camera 114B, right speaker 185A, microphone(s), low-powerwireless circuitry (e.g., for wireless short range network communicationvia Bluetooth™), high-speed wireless circuitry (e.g., for wireless localarea network communication via Wi-Fi).

The right visible-light camera 114B is coupled to or disposed on theflexible PCB 140B and covered by a visible-light camera cover lens,which is aimed through opening(s) formed in the frame 105. For example,the right rim 107B of the frame 105, shown in FIG. 2A, is connected tothe right corner 110B and includes the opening(s) for the visible-lightcamera cover lens. The frame 105 includes a front side configured toface outward and away from the eye of the user. The opening for thevisible-light camera cover lens is formed on and through the front oroutward-facing side of the frame 105. In the example, the rightvisible-light camera 114B has an outward-facing field of view 111B(shown in FIG. 3 ) with a line of sight or perspective that iscorrelated with the right eye of the user of the eyewear device 100. Thevisible-light camera cover lens can also be adhered to a front side oroutward-facing surface of the right corner 110B in which an opening isformed with an outward-facing angle of coverage, but in a differentoutwardly direction. The coupling can also be indirect via interveningcomponents.

As shown in FIG. 1B, flexible PCB 140B is disposed inside the rightcorner 110B and is coupled to one or more other components housed in theright corner 110B. Although shown as being formed on the circuit boardsof the right corner 110B, the right visible-light camera 114B can beformed on the circuit boards of the left corner 110A, the temples 125A,125B, or the frame 105.

FIGS. 2A and 2B are perspective views, from the rear, of examplehardware configurations of the eyewear device 100, including twodifferent types of image displays. The eyewear device 100 is sized andshaped in a form configured for wearing by a user; the form ofeyeglasses is shown in the example. The eyewear device 100 can takeother forms and may incorporate other types of frameworks; for example,a headgear, a headset, or a helmet.

In the eyeglasses example, eyewear device 100 includes a frame 105including a left rim 107A connected to a right rim 107B via a bridge 106adapted to be supported by a nose of the user. The left and right rims107A, 107B include respective apertures 175A, 175B, which hold arespective optical element 180A, 180B, such as a lens and a displaydevice. As used herein, the term “lens” is meant to include transparentor translucent pieces of glass or plastic having curved or flat surfacesthat cause light to converge or diverge or that cause little or noconvergence or divergence.

Although shown as having two optical elements 180A, 180B, the eyeweardevice 100 can include other arrangements, such as a single opticalelement (or it may not include any optical element 180A, 180B),depending on the application or the intended user of the eyewear device100. As further shown, eyewear device 100 includes a left corner 110Aadjacent the left lateral side 170A of the frame 105 and a right corner110B adjacent the right lateral side 170B of the frame 105. The corners110A, 110B may be integrated into the frame 105 on the respective sides170A, 170B (as illustrated) or implemented as separate componentsattached to the frame 105 on the respective sides 170A, 170B.Alternatively, the corners 110A, 110B may be integrated into temples(not shown) attached to the frame 105.

In one example, the image display of optical assembly 180A, 180Bincludes an integrated image display. As shown in FIG. 2A, each opticalassembly 180A, 180B includes a suitable display matrix 177, such as aliquid crystal display (LCD), an organic light-emitting diode (OLED)display, or any other such display. Each optical assembly 180A, 180Balso includes an optical layer or layers 176, which can include lenses,optical coatings, prisms, mirrors, waveguides, optical strips, and otheroptical components in any combination. The optical layers 176A, 176B, .. . 176N (shown as 176A-N in FIG. 2A and herein) can include a prismhaving a suitable size and configuration and including a first surfacefor receiving light from a display matrix and a second surface foremitting light toward the eye of the user. The prism of the opticallayers 176A-N extends over all or at least a portion of the respectiveapertures 175A, 175B formed in the left and right rims 107A, 107B topermit the user to see the second surface of the prism when the eye ofthe user is viewing through the corresponding left and right rims 107A,107B. The first surface of the prism of the optical layers 176A-N facesupwardly from the frame 105 and the display matrix 177 overlies theprism so that photons and light emitted by the display matrix 177impinge the first surface. The prism is sized and shaped so that thelight is refracted within the prism and is directed toward the eye ofthe user by the second surface of the prism of the optical layers176A-N. In this regard, the second surface of the prism of the opticallayers 176A-N can be convex to direct the light toward the center of theeye. The prism can optionally be sized and shaped to magnify the imageprojected by the display matrix 177, and the light travels through theprism so that the image viewed from the second surface is larger in oneor more dimensions than the image emitted from the display matrix 177.

In one example, the optical layers 176A-N may include an LCD layer thatis transparent (keeping the lens open) unless and until a voltage isapplied which makes the layer opaque (closing or blocking the lens). Theimage processor 412 on the eyewear device 100 may execute programming toapply the voltage to the LCD layer in order to produce an active shuttersystem, making the eyewear device 100 suitable for viewing visualcontent when displayed as a three-dimensional projection. Technologiesother than LCD may be used for the active shutter mode, including othertypes of reactive layers that are responsive to a voltage or anothertype of input.

In another example, the image display device of optical assembly 180A,180B includes a projection image display as shown in FIG. 2B. Eachoptical assembly 180A, 180B includes a laser projector 150, which is athree-color laser projector using a scanning mirror or galvanometer.During operation, an optical source such as a laser projector 150 isdisposed in or on one of the temples 125A, 125B of the eyewear device100. Optical assembly 180B in this example includes one or more opticalstrips 155A, 155B, . . . 155N (shown as 155A-N in FIG. 2B) which arespaced apart and across the width of the lens of each optical assembly180A, 180B or across a depth of the lens between the front surface andthe rear surface of the lens.

As the photons projected by the laser projector 150 travel across thelens of each optical assembly 180A, 180B, the photons encounter theoptical strips 155A-N. When a particular photon encounters a particularoptical strip, the photon is either redirected toward the user's eye, orit passes to the next optical strip. A combination of modulation oflaser projector 150, and modulation of optical strips, control specificphotons or beams of light. In an example, a processor controls opticalstrips 155A-N by initiating mechanical, acoustic, or electromagneticsignals. Although shown as having two optical assemblies 180A, 180B, theeyewear device 100 can include other arrangements, such as a single orthree optical assemblies, or each optical assembly 180A, 180B may havearranged different arrangement depending on the application or intendeduser of the eyewear device 100.

In another example, the eyewear device 100 shown in FIG. 2B may includetwo projectors, a left projector (not shown) and a right projector 150.The left optical assembly 180A may include a left display matrix 177 ora left set of optical strips (not shown) which are configured tointeract with light from the left projector. Similarly, the rightoptical assembly 180B may include a right display matrix (not shown) ora right set of optical strips 155A, 155B, . . . 155N which areconfigured to interact with light from the right projector 150. In thisexample, the eyewear device 100 includes a left display and a rightdisplay.

FIG. 3 is a diagrammatic depiction of a three-dimensional (3D) scene306, a left raw image 302A captured by a left visible-light camera 114A,and a right raw image 302B captured by a right visible-light camera114B. The left field of view 111A may overlap, as shown, with the rightfield of view 111B. The overlapping field of view 304 represents thatportion of the image captured by both cameras 114A, 114B. The term‘overlapping’ when referring to field of view means the matrix of pixelsin the generated raw images overlap by thirty percent (30%) or more.‘Substantially overlapping’ means the matrix of pixels in the generatedraw images—or in the infrared image of scene—overlap by fifty percent(50%) or more. As described herein, the two raw images 302A, 302B may beprocessed to include a timestamp, which allows the images to bedisplayed together as part of a three-dimensional projection.

For the capture of stereo images, as illustrated in FIG. 3 , a pair ofraw red, green, and blue (RGB) images are captured of a real scene 306at a given moment in time—a left raw image 302A captured by the leftcamera 114A and right raw image 302B captured by the right camera 114B.When the pair of raw images 302A, 302B are processed (e.g., by the imageprocessor 412), depth images are generated. The generated depth imagesmay be viewed on an optical assembly 180A, 180B of an eyewear device, onanother display (e.g., the image display 580 on a mobile device 401), oron a screen.

In one example, the generated depth images are in the two-dimensional orthree-dimensional space domain and can comprise a matrix of vertices ona multi-dimensional location coordinate system that includes an X axisfor horizontal position (e.g., length), a Y axis for vertical position(e.g., height), and, optionally, a Z axis for depth (e.g., distance).Each vertex may include a color attribute (e.g., a red pixel lightvalue, a green pixel light value, or a blue pixel light value); aposition attribute (e.g., an X location coordinate, a Y locationcoordinate, and optionally a Z location coordinate); a textureattribute; a reflectance attribute; or a combination thereof. Thetexture attribute quantifies the perceived texture of the depth image,such as the spatial arrangement of color or intensities in a region ofvertices of the depth image.

In one example, the HRTF modeling system 400 (FIG. 4 ) includes theeyewear device 100, which includes a frame 105 and a left temple 125Aextending from a left lateral side 170A of the frame 105 and a righttemple 125B extending from a right lateral side 170B of the frame 105.The eyewear device 100 may further include at least two visible-lightcameras 114A, 114B having overlapping fields of view. In one example,the eyewear device 100 includes a left visible-light camera 114A with aleft field of view 111A, as illustrated in FIG. 3 . The left camera 114Ais connected to the frame 105 or the left temple 125A to capture a leftraw image 302A from the left side of scene 306. The eyewear device 100further includes a right visible-light camera 114B with a right field ofview 111B. The right camera 114B is connected to the frame 105 or theright temple 125B to capture a right raw image 302B from the right sideof scene 306.

FIG. 4 is a functional block diagram of an example HRTF modeling system400 that includes a wearable device (e.g., an eyewear device 100), amobile device 401, and a server system 498 connected via variousnetworks 495 such as the Internet. As shown, the HRTF modeling system400 includes a low-power wireless connection 425 and a high-speedwireless connection 437 between the eyewear device 100 and the mobiledevice 401.

As shown in FIG. 4 , the eyewear device 100 includes one or morevisible-light cameras 114A, 114B that capture still images, videoimages, or both still and video images, as described herein. The cameras114A, 114B may have a direct memory access (DMA) to high-speed circuitry430 and function as a stereo camera. The cameras 114A, 114B may be usedto capture initial-depth images that may be rendered intothree-dimensional (3D) models that are texture-mapped images of a red,green, and blue (RGB) imaged scene or respectively displayed on imagedisplay of optical assemblies 180A-B. The device 100 may also include adepth sensor, which uses infrared signals to estimate the position ofobjects relative to the device 100. The depth sensor in some examplesincludes one or more infrared emitter(s) 415 and infrared camera(s) 410.

The eyewear device 100 further includes two image displays of eachoptical assembly 180A, 180B (one associated with the left side 170A andone associated with the right side 170B). The eyewear device 100 alsoincludes an image display driver 442, an image processor 412, low-powercircuitry 420, and high-speed circuitry 430. The image displays of eachoptical assembly 180A, 180B are for presenting images, including stillimages, video images, or still and video images. The image displaydriver 442 is coupled to the image displays of each optical assembly180A, 180B in order to control the display of images.

The eyewear device 100 additionally includes a pair of speakers 185A-B(e.g., one associated with the left side of the eyewear device andanother associated with the right side of the eyewear device). Thespeakers 185A may be incorporated into the frame 105, temples 125, orcorners 110 of the eyewear device 100. The speakers 185 are driven byaudio processor 413 under control of low-power circuitry 420, high-speedcircuitry 430, or both. The speakers 185 are for presenting audiosignals including, for example, an audio track associated with a virtualobject. The audio processor 413 is coupled to the speakers 185 in orderto control the presentation of sound in accordance with HRTF modeling toprovide acoustical position information corresponding to the location ofvirtual objects presented on the image displays of optical assemblies180A-B. Audio processor 413 may be any processor capable of managingaudio processing needed for eyewear device 100 (e.g., capable of HRTFmodeling).

The components shown in FIG. 4 for the eyewear device 100 are located onone or more circuit boards, for example a printed circuit board (PCB) orflexible printed circuit (FPC), located in the rims or temples.Alternatively, or additionally, the depicted components can be locatedin the corners, frames, hinges, or bridge of the eyewear device 100.Left and right visible-light cameras 114A, 114B can include digitalcamera elements such as a complementary metal-oxide-semiconductor (CMOS)image sensor, a charge-coupled device, a lens, or any other respectivevisible or light capturing elements that may be used to capture data,including still images or video of scenes with unknown objects.

As shown in FIG. 4 , high-speed circuitry 430 includes a high-speedprocessor 432, a memory 434, and high-speed wireless circuitry 436. Inthe example, the image display driver 442 is coupled to the high-speedcircuitry 430 and operated by the high-speed processor 432 in order todrive the left and right image displays of each optical assembly 180A,180B. High-speed processor 432 may be any processor capable of managinghigh-speed communications and operation of any general computing systemneeded for eyewear device 100. High-speed processor 432 includesprocessing resources needed for managing high-speed data transfers onhigh-speed wireless connection 437 to a wireless local area network(WLAN) using high-speed wireless circuitry 436.

In some examples, the high-speed processor 432 executes an operatingsystem such as a LINUX operating system or other such operating systemof the eyewear device 100 and the operating system is stored in memory434 for execution. In addition to any other responsibilities, thehigh-speed processor 432 executes a software architecture for theeyewear device 100 that is used to manage data transfers with high-speedwireless circuitry 436. In some examples, high-speed wireless circuitry436 is configured to implement Institute of Electrical and ElectronicEngineers (IEEE) 802.11 communication standards, also referred to hereinas Wi-Fi. In other examples, other high-speed communications standardsmay be implemented by high-speed wireless circuitry 436.

The low-power circuitry 420 includes a low-power processor 422 andlow-power wireless circuitry 424. The low-power wireless circuitry 424and the high-speed wireless circuitry 436 of the eyewear device 100 caninclude short-range transceivers (Bluetooth™ or Bluetooth Low-Energy(BLE)) and wireless wide, local, or wide-area network transceivers(e.g., cellular or Wi-Fi). Mobile device 401, including the transceiverscommunicating via the low-power wireless connection 425 and thehigh-speed wireless connection 437, may be implemented using details ofthe architecture of the eyewear device 100, as can other elements of thenetwork 495.

Memory 434 includes any storage device capable of storing various dataand applications, including, among other things, camera data generatedby the left and right visible-light cameras 114A, 114B, the infraredcamera(s) 410, the image processor 412, and images generated for displayby the image display driver 442 on the image display of each opticalassembly 180A, 180B. Although the memory 434 is shown as integrated withhigh-speed circuitry 430, the memory 434 in other examples may be anindependent, standalone element of the eyewear device 100. In certainsuch examples, electrical routing lines may provide a connection througha chip that includes the high-speed processor 432 from the imageprocessor 412 or low-power processor 422 to the memory 434. In otherexamples, the high-speed processor 432 may manage addressing of memory434 such that the low-power processor 422 will boot the high-speedprocessor 432 any time that a read or write operation involving memory434 is needed.

As shown in FIG. 4 , the high-speed processor 432 of the eyewear device100 can be coupled to the camera system (visible-light cameras 114A,114B), the image display driver 442, the user input device 491, and thememory 434. As shown in FIG. 5 , the CPU 530 of the mobile device 401may be coupled to a camera system 570, a mobile display driver 582, auser input layer 591, and a memory 540A.

The server system 498 may be one or more computing devices as part of aservice or network computing system, for example, that include aprocessor, a memory, and network communication interface to communicateover the network 495 with an eyewear device 100 and a mobile device 401.

The output components of the eyewear device 100 include visual elements,such as the left and right image displays associated with each lens oroptical assembly 180A, 180B as described in FIGS. 2A and 2B (e.g., adisplay such as a liquid crystal display (LCD), a plasma display panel(PDP), a light emitting diode (LED) display, a projector, or awaveguide). The eyewear device 100 may include a user-facing indicator(e.g., an LED, a loudspeaker, or a vibrating actuator), or anoutward-facing signal (e.g., an LED, a loudspeaker). The image displaysof each optical assembly 180A, 180B are driven by the image displaydriver 442. The output components of the eyewear device 100 furtherinclude additional indicators such as audible elements (e.g., speakers185A-B under control of audio processor 413), tactile components (e.g.,an actuator such as a vibratory motor to generate haptic feedback), andother signal generators. For example, the device 100 may include auser-facing set of indicators, and an outward-facing set of signals. Theuser-facing set of indicators are configured to be seen or otherwisesensed by the user of the device 100. For example, the device 100 mayinclude an LED display positioned so the user can see it, a one or morespeakers positioned to generate a sound the user can hear, or anactuator to provide haptic feedback the user can feel. Theoutward-facing set of signals are configured to be seen or otherwisesensed by an observer near the device 100. Similarly, the device 100 mayinclude an LED, a loudspeaker, or an actuator that is configured andpositioned to be sensed by an observer.

The input components of the eyewear device 100 may include alphanumericinput components (e.g., a touch screen or touchpad configured to receivealphanumeric input, a photo-optical keyboard, or otheralphanumeric-configured elements), pointer-based input components (e.g.,a mouse, a touchpad, a trackball, a joystick, a motion sensor, or otherpointing instruments), tactile input components (e.g., a button switch,a touch screen or touchpad that senses the location, force or locationand force of touches or touch gestures, or other tactile-configuredelements), visual input (e.g., hand gestures captured via cameras114A-B), and audio input components (e.g., a microphone), and the like.The mobile device 401 and the server system 498 may includealphanumeric, pointer-based, tactile, audio, visual, and other inputcomponents.

In some examples, the eyewear device 100 includes a collection ofmotion-sensing components referred to as an inertial measurement unit472. The motion-sensing components may be micro-electro-mechanicalsystems (MEMS) with microscopic moving parts, often small enough to bepart of a microchip. The inertial measurement unit (IMU) 472 in someexample configurations includes an accelerometer, a gyroscope, and amagnetometer. The accelerometer senses the linear acceleration of thedevice 100 (including the acceleration due to gravity) relative to threeorthogonal axes (x, y, z). The gyroscope senses the angular velocity ofthe device 100 about three axes of rotation (pitch, roll, yaw).Together, the accelerometer and gyroscope can provide position,orientation, and motion data about the device relative to six axes (x,y, z, pitch, roll, yaw). The magnetometer, if present, senses theheading of the device 100 relative to magnetic north. The position ofthe device 100 may be determined by location sensors, such as a GPS unit473, one or more transceivers to generate relative position coordinates,altitude sensors or barometers, and other orientation sensors. Suchpositioning system coordinates can also be received over the wirelessconnections 425, 437 from the mobile device 401 via the low-powerwireless circuitry 424 or the high-speed wireless circuitry 436.

The IMU 472 may include or cooperate with a digital motion processor orprogramming that gathers the raw data from the components and compute anumber of useful values about the position, orientation, and motion ofthe device 100. For example, the acceleration data gathered from theaccelerometer can be integrated to obtain the velocity relative to eachaxis (x, y, z); and integrated again to obtain the position of thedevice 100 (in linear coordinates, x, y, and z). The angular velocitydata from the gyroscope can be integrated to obtain the position of thedevice 100 (in spherical coordinates). The programming for computingthese useful values may be stored in memory 434 and executed by thehigh-speed processor 432 of the eyewear device 100.

The eyewear device 100 may optionally include additional peripheralsensors, such as biometric sensors, specialty sensors, or displayelements integrated with eyewear device 100. For example, peripheraldevice elements may include any I/O components including outputcomponents, motion components, position components, or any other suchelements described herein. For example, the biometric sensors mayinclude components to detect expressions (e.g., hand expressions, facialexpressions, vocal expressions, body gestures, or eye tracking), tomeasure bio signals (e.g., blood pressure, heart rate, body temperature,perspiration, or brain waves), or to identify a person (e.g.,identification based on voice, retina, facial characteristics,fingerprints, or electrical bio signals such as electroencephalogramdata), and the like.

The mobile device 401 may be a smartphone, tablet, laptop computer,access point, or any other such device capable of connecting witheyewear device 100 using both a low-power wireless connection 425 and ahigh-speed wireless connection 437. Mobile device 401 is connected toserver system 498 and network 495. The network 495 may include anycombination of wired and wireless connections.

The HRTF modeling system 400, as shown in FIG. 4 , includes a computingdevice, such as mobile device 401, coupled to an eyewear device 100 overa network. The HRTF modeling system 400 includes a memory for storinginstructions and a processor for executing the instructions. Executionof the instructions of the HRTF modeling system 400 by the processor 432configures the eyewear device 100 to act alone or cooperate with one ormore other computing device, e.g., the mobile device 401 or the serversystem 498. The HRTF modeling system 400 may utilize the memory 434 ofthe eyewear device 100 or the memory elements 540A, 540B, 540C of themobile device 401 (FIG. 5 ). Also, the HRTF modeling system 400 mayutilize the processor elements 432, 422 of the eyewear device 100 or thecentral processing unit (CPU) 530 of the mobile device 401 (FIG. 5 ). Inaddition, the HRTF modeling system 400 may further utilize the memoryand processor elements of the server system 498. In this aspect, thememory and processing functions of the HRTF modeling system 400 can beshared or distributed across the eyewear device 100, the mobile device401, and the server system 498.

The memory 434, in some example implementations, includes a hand gesturelibrary 480. The library of hand gestures 480 includes poses andgestures, with the hand in various positions and orientations. Thestored poses and gestures are suitable for comparison to a hand shapethat is detected in an image. The library 480 includes three-dimensionalcoordinates for landmarks of the hand, e.g., from the wrist to thefingertips, for use in matching. For example, a hand gesture recordstored in the library 480 may include a hand gesture identifier (e.g.,pointing finger, closed fist, open palm, relaxed hand, grasping anobject, pinching, spreading), a point of view or a directional reference(e.g., palmar side visible, dorsal, lateral), and other informationabout orientation, along with three-dimensional coordinates for thewrist, the fifteen interphalangeal joints, the five fingertips and otherskeletal or soft-tissue landmarks. The process of detecting a handshape, in some implementations, involves comparing the pixel-level datain one or more captured frames of video data to the hand gestures storedin the library 480 until a match is found, e.g., by applying a machinevision algorithm. A match may be determined when a predefined confidencethreshold set in the machine vision algorithm is exceeded.

The memory 434 additionally includes, in some example implementations,audio filters 481, a virtual object database 482, a virtual objectprocessing system 484, an audio zone detection system 486, and an audioprocession system 488.

The audio filters 481 include multiple predefined HRTF audio filters(e.g., a left audio filter and a right audio filter for each zone) forprocessing a virtual object audio track based on its position. In oneexample, the HRTF equalization and delay needed for any zone ispre-calculated as a small set of biquad filters (e.g., 4-7 biquadfilters per zone; where each filter represents 6 multiply-and-accumulateoperations). A digital biquadratic (biquad) filter is a second orderrecursive linear filter, containing two poles and two zeros. In the Zdomain, a biquad filter's transfer function is the ratio of twoquadratic functions (H(z)=(b₀+b₁z⁻¹+b₂z⁻²)/(a₀+a₁z⁻¹+a₂z⁻²)).

The virtual object database 482 includes information associated withvirtual objects. In one example, the virtual object database 482includes audio information (e.g., an audio track) and visual information(e.g., images for creating appearance).

The virtual object processing system 484 generates instructions forpresenting virtual objects on the image display of optical assembly180A-B and controlling movement of the virtual objects. The virtualobject processing system 484 additionally calculates informationassociated with the virtual object such as its position, directionalvelocity, and distance with respect to the user. The audio zonedetection system 486, generates instructions for detecting which zonethe virtual object is currently in with respect to the head of a user.In one example the audio zone detection system 484 maintains a map (seeFIG. 8A) representing the zones surrounding a head of a user for use inzone detection. The audio processing system 488 generates instructionsfor applying HRTF filters to the audio tracks of the virtual objectsresponsive to their current position and presenting sound to the uservia audio processor 413 and speakers 185A-B.

The memory 434 may additionally include an image capture application, alocalization system, and an image processing system. In an HRTF modelingsystem 400 in which a camera is capturing frames of video data, theimage capture application configures the processor 432 to detect a handshape (e.g., a pointing index finger). The localization systemconfigures the processor 432 to obtain localization data for use indetermining the position of the eyewear device 100 relative to thephysical environment. The localization data may be derived from a seriesof images, an IMU 472, a GPS unit, or a combination thereof. The imageprocessing system configures the processor 432 to present a capturedstill image on a display of an optical assembly 180A-B in cooperationwith the image display driver 442 and the image processor 412.

FIG. 5 is a high-level functional block diagram of an example mobiledevice 401. Mobile device 401 includes a flash memory 540A which storesprogramming to be executed by the CPU 530 to perform all or a subset ofthe functions described herein.

The mobile device 401 may include a camera 570 that comprises at leasttwo visible-light cameras (first and second visible-light cameras withoverlapping fields of view) or at least one visible-light camera and adepth sensor with substantially overlapping fields of view. Flash memory540A may further include multiple images or video, which are generatedvia the camera 570.

As shown, the mobile device 401 includes an image display 580, a mobiledisplay driver 582 to control the image display 580, and a displaycontroller 584. In the example of FIG. 5 , the image display 580includes a user input layer 591 (e.g., a touchscreen) that is layered ontop of or otherwise integrated into the screen used by the image display580.

Examples of touchscreen-type mobile devices that may be used include(but are not limited to) a smart phone, a personal digital assistant(PDA), a tablet computer, a laptop computer, or other portable device.However, the structure and operation of the touchscreen-type devices isprovided by way of example; the subject technology as described hereinis not intended to be limited thereto. For purposes of this discussion,FIG. 5 therefore provides a block diagram illustration of the examplemobile device 401 with a user interface that includes a touchscreeninput layer 591 for receiving input (by touch, multi-touch, or gesture,and the like, by hand, stylus or other tool) and an image display 580for displaying content

As shown in FIG. 5 , the mobile device 401 includes at least one digitaltransceiver (XCVR) 510, shown as WWAN XCVRs, for digital wirelesscommunications via a wide-area wireless mobile communication network.The mobile device 401 also includes additional digital or analogtransceivers, such as short-range transceivers (XCVRs) 520 forshort-range network communication, such as via NFC, VLC, DECT, ZigBee,Bluetooth™, or Wi-Fi. For example, short range XCVRs 520 may take theform of any available two-way wireless local area network (WLAN)transceiver of a type that is compatible with one or more standardprotocols of communication implemented in wireless local area networks,such as one of the Wi-Fi standards under IEEE 802.11.

To generate location coordinates for positioning of the mobile device401, the mobile device 401 can include a global positioning system (GPS)receiver. Alternatively, or additionally the mobile device 401 canutilize either or both the short range XCVRs 520 and WWAN XCVRs 510 forgenerating location coordinates for positioning. For example, cellularnetwork, Wi-Fi, or Bluetooth™ based positioning systems can generatevery accurate location coordinates, particularly when used incombination. Such location coordinates can be transmitted to the eyeweardevice over one or more network connections via XCVRs 510, 520.

The transceivers 510, 520 (i.e., the network communication interface)conforms to one or more of the various digital wireless communicationstandards utilized by modern mobile networks. Examples of WWANtransceivers 510 include (but are not limited to) transceiversconfigured to operate in accordance with Code Division Multiple Access(CDMA) and 3rd Generation Partnership Project (3GPP) networktechnologies including, for example and without limitation, 3GPP type 2(or 3GPP2) and LTE, at times referred to as “4G.” For example, thetransceivers 510, 520 provide two-way wireless communication ofinformation including digitized audio signals, still image and videosignals, web page information for display as well as web-related inputs,and various types of mobile message communications to/from the mobiledevice 401.

The mobile device 401 further includes a microprocessor that functionsas a central processing unit (CPU); shown as CPU 530 in FIG. 4 . Aprocessor is a circuit having elements structured and arranged toperform one or more processing functions, typically various dataprocessing functions. Although discrete logic components could be used,the examples utilize components forming a programmable CPU. Amicroprocessor for example includes one or more integrated circuit (IC)chips incorporating the electronic elements to perform the functions ofthe CPU. The CPU 530, for example, may be based on any known oravailable microprocessor architecture, such as a Reduced Instruction SetComputing (RISC) using an ARM architecture, as commonly used today inmobile devices and other portable electronic devices. Of course, otherarrangements of processor circuitry may be used to form the CPU 530 orprocessor hardware in smartphone, laptop computer, and tablet.

The CPU 530 serves as a programmable host controller for the mobiledevice 401 by configuring the mobile device 401 to perform variousoperations, for example, in accordance with instructions or programmingexecutable by CPU 530. For example, such operations may include variousgeneral operations of the mobile device, as well as operations relatedto the programming for applications on the mobile device. Although aprocessor may be configured by use of hardwired logic, typicalprocessors in mobile devices are general processing circuits configuredby execution of programming.

The mobile device 401 includes a memory or storage system, for storingprogramming and data. In the example, the memory system may include aflash memory 540A, a random-access memory (RAM) 540B, and other memorycomponents 540C, as needed. The RAM 540B serves as short-term storagefor instructions and data being handled by the CPU 530, e.g., as aworking data processing memory. The flash memory 540A typically provideslonger-term storage.

Hence, in the example of mobile device 401, the flash memory 540A isused to store programming or instructions for execution by the CPU 530.Depending on the type of device, the mobile device 401 stores and runs amobile operating system through which specific applications areexecuted. Examples of mobile operating systems include Google Android,Apple iOS (for iPhone or iPad devices), Windows Mobile, Amazon Fire OS,RIM BlackBerry OS, or the like.

The processor 432 within the eyewear device 100 may construct a map ofthe environment surrounding the eyewear device 100, determine a locationof the eyewear device within the mapped environment, and determine arelative position of the eyewear device to one or more objects in themapped environment. The processor 432 may construct the map anddetermine location and position information using a simultaneouslocalization and mapping (SLAM) algorithm applied to data received fromone or more sensors. Sensor data includes images received from one orboth of the cameras 114A, 114B, distance(s) received from a laser rangefinder, position information received from a GPS unit 473, motion andacceleration data received from an IMU 572, or a combination of datafrom such sensors, or from other sensors that provide data useful indetermining positional information. In the context of augmented reality,a SLAM algorithm is used to construct and update a map of anenvironment, while simultaneously tracking and updating the location ofa device (or a user) within the mapped environment. The mathematicalsolution can be approximated using various statistical methods, such asparticle filters, Kalman filters, extended Kalman filters, andcovariance intersection. In a system that includes a high-definition(HD) video camera that captures video at a high frame rate (e.g., thirtyframes per second), the SLAM algorithm updates the map and the locationof objects at least as frequently as the frame rate; in other words,calculating and updating the mapping and localization thirty times persecond.

Sensor data includes image(s) received from one or both cameras 114A,114B, distance(s) received from a laser range finder, positioninformation received from a GPS unit 473, motion and acceleration datareceived from an IMU 472, or a combination of data from such sensors, orfrom other sensors that provide data useful in determining positionalinformation.

FIG. 6 depicts an example physical environment 600 along with elementsthat are useful for natural feature tracking (NFT; e.g., a trackingapplication using a SLAM algorithm). A user 602 of eyewear device 100 ispresent in an example physical environment 600 (which, in FIG. 6 , is aninterior room). The processor 432 of the eyewear device 100 determinesits position with respect to one or more objects 604 within theenvironment 600 using captured images, constructs a map of theenvironment 600 using a coordinate system (x, y, z) for the environment600, and determines its position within the coordinate system.Additionally, the processor 432 determines a head pose (roll, pitch, andyaw) of the eyewear device 100 within the environment by using two ormore location points (e.g., three location points 606 a, 606 b, and 606c) associated with a single object 604 a, or by using one or morelocation points 606 associated with two or more objects 604 a, 604 b,604 c. The processor 432 of the eyewear device 100 may position avirtual object 608 (such as the key shown in FIG. 6 ) within theenvironment 600 for viewing during an augmented reality experience.

Markers 610 are registered at locations in the environment to assistdevices with the task of tracking and updating the location of users,devices, and objects (virtual and physical) in a mapped environment.Markers are sometimes registered to a high-contrast physical object,such as the relatively dark object, such as the framed picture 604 a,mounted on a lighter-colored wall, to assist cameras and other sensorswith the task of detecting the marker. The markers may be preassigned ormay be assigned by the eyewear device 100 upon entering the environment.

Markers 610 can be encoded with or otherwise linked to information. Amarker may include position information, a physical code (such as a barcode or a QR code), or a combination thereof and may be either visibleto the user or hidden. A set of data associated with each marker 610 isstored in the memory 434 of the eyewear device 100. The set of dataincludes information about the marker 610 a, the marker's position(location and orientation), one or more virtual objects, or acombination thereof. The marker position may include three-dimensionalcoordinates for one or more marker landmarks 616 a, such as the cornerof the generally rectangular marker 610 a shown in FIG. 6 . The markerlocation may be expressed relative to real-world geographic coordinates,a system of marker coordinates, a position of the eyewear device 100, orother coordinate system. The one or more virtual objects associated withthe marker 610 a may include any of a variety of material, includingstill images, video, audio, tactile feedback, executable applications,interactive user interfaces and experiences, and combinations orsequences of such material. Any type of content capable of being storedin a memory, retrieved when the marker 610 a is encountered, orassociated with an assigned marker may be classified as a virtual objectin this context. The key 608 shown in FIG. 6 , for example, is a virtualobject displayed as a still image, either 2D or 3D, at a markerlocation.

In one example, the marker 610 a may be registered in memory as beinglocated near and associated with a physical object 604 a (e.g., theframed work of art shown in FIG. 6 ). In another example, the marker maybe registered in memory as being a particular position with respect tothe eyewear device 100.

FIG. 7 is a flow chart 700 depicting a method for implementing augmentedreality applications described herein on a wearable device (e.g., aneyewear device). Although the steps are described with reference to theeyewear device 100, as described herein, other implementations of thesteps described, for other types of devices, will be understood by oneof skill in the art from the description herein. Additionally, it iscontemplated that one or more of the steps shown in FIG. 7 , and inother figures, and described herein may be omitted, performedsimultaneously or in a series, performed in an order other thanillustrated and described, or performed in conjunction with additionalsteps.

At block 702, the eyewear device 100 captures one or more input imagesof a physical environment 600 near the eyewear device 100. The processor432 may continuously receive input images from the visible lightcamera(s) 114 and store those images in memory 434 for processing.Additionally, the eyewear device 100 may capture information from othersensors (e.g., location information from a GPS unit, orientationinformation from an IMU 472, or distance information from a laserdistance sensor).

At block 704, the eyewear device 100 compares objects in the capturedimages to objects stored in a library of images to identify a match. Insome implementations, the processor 432 stores the captured images inmemory 434. A library of images of known objects is stored in a virtualobject database 482.

In one example, the processor 432 is programmed to identify a predefinedparticular object (e.g., a particular picture 604 a hanging in a knownlocation on a wall, a window 604 b in another wall, or an object such asa safe 604 c positioned on the floor). Other sensor data, such as GPSdata, may be used to narrow down the number of known objects for use inthe comparison (e.g., only images associated with a room identifiedthrough GPS coordinates). In another example, the processor 432 isprogrammed to identify predefined general objects (such as one or moretrees within a park).

At block 706, the eyewear device 100 determines its position withrespect to the object(s). The processor 432 may determine its positionwith respect to the objects by comparing and processing distancesbetween two or more points in the captured images (e.g., between two ormore location points on one objects 604 or between a location point 606on each of two objects 604) to known distances between correspondingpoints in the identified objects. Distances between the points of thecaptured images greater than the points of the identified objectsindicates the eyewear device 100 is closer to the identified object thanthe imager that captured the image including the identified object. Onthe other hand, distances between the points of the captured images lessthan the points of the identified objects indicates the eyewear device100 is further from the identified object than the imager that capturedthe image including the identified object. By processing the relativedistances, the processor 432 is able to determine the position withinrespect to the objects(s). Alternatively, or additionally, other sensorinformation, such as laser distance sensor information, may be used todetermine position with respect to the object(s).

At block 708, the eyewear device 100 constructs a map of an environment600 surrounding the eyewear device 100 and determines its locationwithin the environment. In one example, where the identified object(block 704) has a predefined coordinate system (x, y, z), the processor432 of the eyewear device 100 constructs the map using that predefinedcoordinate system and determines its position within that coordinatesystem based on the determined positions (block 706) with respect to theidentified objects. In another example, the eyewear device constructs amap using images of permanent or semi-permanent objects 604 within anenvironment (e.g., a tree or a park bench within a park). In accordancewith this example, the eyewear device 100 may define the coordinatesystem (x′, y′, z′) used for the environment.

At block 710, the eyewear device 100 determines a head pose (roll,pitch, and yaw) of the eyewear device 100 within the environment. Theprocessor 432 determines head pose by using two or more location points(e.g., three location points 606 a, 606 b, and 606 c) on one or moreobjects 604 or by using one or more location points 606 on two or moreobjects 604. Using conventional image processing algorithms, theprocessor 432 determines roll, pitch, and yaw by comparing the angle andlength of a lines extending between the location points for the capturedimages and the known images.

At block 712, the eyewear device 100 presents visual images to the user.The processor 432 presents images to the user on the image displays 180using the image processor 412 and the image display driver 442. Theprocessor develops and presents the visual images via the image displaysresponsive to the location of the eyewear device 100 within theenvironment 600. In one example, the visual images include an image of ahand 1002 for manipulating features of a GUI (FIG. 8B) and a virtualspace craft 1004 (FIG. 10 ).

At block 714, the steps described above with reference to blocks 706-712are repeated to update the position of the eyewear device 100 and whatis viewed by the user 602 as the user moves through the environment 600.

FIG. 8A is an illustration representing a zone map 800 with objects (36objects in FIG. 8A) positioned in each of multiple zones surrounding theobjects (e.g., 36 zones; not illustrated) around a user for use inselecting HRTF filters to apply to audio tracks for presentation at anear 803 of the user. The zone map defines the boundary of each zone. Inan example, the space around the head 802 of the user is defined into 36zones: 12 sectors rotationally around the head (like a clock), with eachsector broken into 3 vertical zones: above ear 808, at ear level 804,and below ear 812. Objects 806 a-n are positioned within respectivezones around the user at ear level 804, objects 810 a-n are positionedwithin respective zones around the user above ear level 808, objects 814a-n are positioned within respective zones around the user below earlevel 812.

FIG. 8B is a graphical user interface (GUI) 850 for testing the filtersapplied to an audio track of a virtual object responsive to the positionof the object with respect to the head 802 of the user. A clock 852 ispresent around the head 802 of the user to represent the 12sectors/zones surrounding the head 802. A circular control 854 and alinear control 860 are present to select the filters to apply to anaudio track to make a sound appear as if it is coming from differentlocations around the head 802 the user. The circular control 854 selectthe direction of the sound in a plane surrounding the head 802 and thelinear control 860 selects the whether the sound is at ear level, aboveear level, or below ear level. Manipulating the controls selects filtersto make sound appear as if it is coming from the desired direction.

The circular control 854 is present around the clock 852. The circularcontrol includes a circular track 858 and a selector 856 positionedwithin the track 858 for selecting a direction. The illustrated selector856 includes an indicator representing angular information associatedwith the desired direction from which the sound should be perceived ascoming from (90 degrees in the illustrated example representing that thesound should appear as if it is coming from the right side of the user).A user moves the selector 856 around the circular track 858 to changethe direction selection.

The linear control 860 includes a linear track 864. A selector 862 ispositioned within the track 864 for selecting the level (e.g., earlevel, below ear level, above ear level). A user moves the selector 862along the track 864 to change the level.

The GUI 850 additionally includes an audio selection button 866 forselecting an audio track, a play button 868 for playing the selectionaudio track, a pause button 870 for pausing the audio track, and a resetbutton 872 for resetting the indicators 856/862 to their defaultlocations (e.g., selection 856 at 90 degrees and selector 862 at 0degrees).

The GUI may be presented on the display 180 of the eyewear device 100,the display 580 of the mobile device 401 or the display for a remotecomputer such as a server system 498. In one example, a user maymanipulate the selectors 856/862 and actuate the buttons 866/868/870/872using a user input device 491 of the eyewear device 100, using userinput layer 591 of the mobile device, or a user input of another device.

In another example, a user may manipulate the selectors 856/862 andactuate the buttons 866/868/870/872 through hand gestures captured bythe cameras 114 of the eyewear device. In accordance with this example,the processor 432 of an eyewear device 100 is configured to captureframes of video data with a camera 114A, 114B. Objects in the images arecompared to the hand gesture library 480 to identify predefined handgestures (e.g., a pointing index finger) associated with an action. Whena hand gesture is identified, its position is determined with respect tothe selectors 856/862 and actuate the buttons 866/868/870/872. Amodification of the hand gesture (e.g., a tapping motion when the tip ofthe index finger is near a button or a swiping motion when the tip ofthe index finger is near a selector) results in an actuation of thebuttons/selector.

The process of determining whether a detected hand shape matches apredefined gesture, in some implementations, involves comparing thepixel-level data about the hand shape in one or more captured frames ofvideo data to the collection of hand gestures stored in the hand gesturelibrary 480. The detected hand shape data may include three-dimensionalcoordinates for the wrist, up to fifteen interphalangeal joints, up fivefingertips, and other skeletal or soft-tissue landmarks found in acaptured frame. These data are compared to hand gesture data stored inthe hand gesture library 480 until the best match is found. In someexamples, the process includes calculating the sum of the geodesicdistances between the detected hand shape fingertip coordinates and aset of fingertip coordinates for each hand gesture stored in the library480. A sum that is within a configurable threshold accuracy valuerepresents a match.

In another example implementation, the process of determining whether adetected hand shape matches a predefined gesture, involves using amachine-learning algorithm to compare the pixel-level data about thehand shape in one or more captured frames of video data to a collectionof images that include hand gestures.

Machine learning refers to an algorithm that improves incrementallythrough experience. By processing a large number of different inputdatasets, a machine-learning algorithm can develop improvedgeneralizations about particular datasets, and then use thosegeneralizations to produce an accurate output or solution whenprocessing a new dataset. Broadly speaking, a machine-learning algorithmincludes one or more parameters that will adjust or change in responseto new experiences, thereby improving the algorithm incrementally; aprocess similar to learning.

In the context of computer vision, mathematical models attempt toemulate the tasks accomplished by the human visual system, with the goalof using computers to extract information from an image and achieve anaccurate understanding of the contents of the image. Computer visionalgorithms have been developed for a variety of fields, includingartificial intelligence and autonomous navigation, to extract andanalyze data in digital images and video.

Deep learning refers to a class of machine-learning methods that arebased on or modeled after artificial neural networks. An artificialneural network is a computing system made up of a number of simple,highly interconnected processing elements (nodes), which processinformation by their dynamic state response to external inputs. A largeartificial neural network might have hundreds or thousands of nodes.

A convolutional neural network (CNN) is a type of neural network that isfrequently applied to analyzing visual images, including digitalphotographs and video. The connectivity pattern between nodes in a CNNis typically modeled after the organization of the human visual cortex,which includes individual neurons arranged to respond to overlappingregions in a visual field. A neural network that is suitable for use inthe determining process described herein is based on one of thefollowing architectures: VGG16, VGG19, ResNet50, Inception V3, Xception,or other CNN-compatible architectures.

In the machine-learning example, the processor 432 determines whether adetected hand shape substantially matches a predefined gesture using amachine-trained algorithm referred to as a hand feature model. Theprocessor 432 is configured to access the hand feature model, trainedthrough machine learning, and applies the hand feature model to identifyand locate features of the hand shape in one or more frames of the videodata.

In one example implementation, the trained hand feature model receives aframe of video data which contains a detected hand shape and abstractsthe image in the frame into layers for analysis. Data in each layer iscompared to hand gesture data stored in the hand gesture library 480,layer by layer, based on the trained hand feature model, until a goodmatch is identified.

In one example, the layer-by-layer image analysis is executed using aconvolutional neural network. In a first convolution layer, the CNNidentifies learned features (e.g., hand landmarks, sets of jointcoordinates, and the like). In a second convolution layer, the image istransformed into a plurality of images, in which the learned featuresare each accentuated in a respective sub-image. In a pooling layer, thesizes and resolution of the images and sub-images are reduced in orderisolation portions of each image that include a possible feature ofinterest (e.g., a possible palm shape, a possible finger joint). Thevalues and comparisons of images from the non-output layers are used toclassify the image in the frame. Classification, as used herein, refersto the process of using a trained model to classify an image accordingto the detected hand shape. For example, an image may be classified as“pointer gesture present” if the detected hand shape matches the pointergesture from the library 480.

In some example implementations, the processor 432, in response todetecting a pointing gesture, presents on the display 180A-B anindicator 1002 (see FIG. 10 ). The indicator 1002 informs the wearerthat a predefined gesture has been detected. The indicator 1002 in oneexample is an object, such as the pointing finger shown in FIG. 10 . Theindicator 1002 may include one or more visible, audible, tactile, andother elements to inform or alert the wearer that a pointer gesture hasbeen detected. A user may move the indicator 1002 by moving the detectedhand gesture within the field of view of the eyewear device 100.

FIG. 9A is a flow chart 900 listing the steps in an example method forpresenting audio signals using a HRTF. Although the steps are describedwith reference to the eyewear device 100, as described herein, otherimplementations of the steps described, for other types of mobiledevices, will be understood by one of skill in the art from thedescription herein. Additionally, it is contemplated that one or more ofthe steps shown and described may be omitted, performed simultaneouslyor in a series, performed in an order other than illustrated anddescribed, or performed in conjunction with additional steps.

At block 902, the system presents a virtual object (e.g., spacecraft1004 in FIG. 10 ). In an example, the processor 432 retrieves a virtualobject from the virtual object database 482. The retrieved virtualobject has an associated audio track. The processor 432 processes thevirtual object using the virtual object processing system 484, whichcontrols the image processor 412 to present the virtual object as imageson displays of the optical assembly 180A-B. The presented virtual objecthas a virtual position in three-dimensional space, which the virtualobject process system 484 tracks.

At block 904, the system determines a current position (direction andoptionally distance) of a virtual object with respect to the head of theuser where the virtual object has an associated audio track. The currentposition includes a direction with respect to the head of the user. Thecurrent position may additionally include a distance with respect to thehead of the user. In one example, the direction and distance arerepresented by a vector the virtual object processing system 484calculates that intersects a position associated with the head of theuser and the virtual position of the virtual object tracked by thevirtual object processing system 484.

At block 906, the system identifies an audio zone responsive to thedetermined position. The processor 432 determines the audio zone usingthe audio zone detection system 486. In one example, the audio zonedetection system 486 retrieves a 3D audio zone map, which includes aspherical shape surrounding an origin representing a location adjacent,on, or within the head of the wearer where the spherical shape isdivided into multiple audio zones (e.g., 36 audio zones). The audio zonedetection system 486 then projects the vector calculated at block 904from the origin and calculates the intersection between the vector andthe audio zone map. To identify the current audio zone, the audio zonedetection system 486 finally identifies the intersected zone as thecurrent audio zone of the virtual object.

At block 908, the system applies the left and the right predefinedfilters corresponding to the current audio zone to the audio trackassociated with the virtual object to produce the left audio signal andthe right audio signal. The processor 432 applies the correspondingpredefined filters to the audio track of the virtual object. In oneexample, the audio processing system 488 retrieves the audio filtercorresponding to the zone from the audio filters 481 stored in thememory 434. The audio processing system 488 then applies the retrievedfilters to the audio track produce a left audio signal and a right audiosignal.

At block 910, the system presents the left audio signal with the firstspeaker and the right audio signal with the second speaker. Theprocessor 432 presents the left audio signal with the first speaker 185A(e.g., to the left ear of the user) and the right audio signal with thesecond speaker 185B (e.g., to the right ear of the user). In an example,the audio processing system 488 instructs the audio processor 413 topresent the left audio signal to the first speaker 185A and the rightaudio signal to the second speaker 185B.

FIG. 9B is a flow chart 920 listing steps in an example method foradjusting the audio track of the virtual object to produce audio signalscorresponding to the directional velocity of the virtual object withrespect to the head of the user. The adjustments provide a morerealistic audio experience that matches the visual interpretation by theuser.

At block 922, the system determines a directional velocity of thevirtual object with respect to the head of the user. The systemdetermines the directional velocity by monitoring movement of thecurrent position of the virtual object over time. In one example, thevirtual object processing system 484 periodically (e.g., every 10 ms)calculates the current position of the virtual object (e.g., asdescribed above with reference to block 904). The virtual objectprocessing system 484 then calculates a directional component between aprior (e.g., an immediately prior) position of the virtual object and acurrent position where the directional component is along a lineextending between the origin associated with the head of the user and aposition adjacent the virtual object to obtain a relative velocity ofthe object with respect to the user.

At block 924, the system adjusts frequencies of the left audio signaland the right audio signal responsive to the determined directionalvelocity. The processor 432 adjusts the frequency of the left audiosignal and the right audio signal. In an example, the audio processingsystem 488 instructs the audio processor 413 to adjust the frequency(e.g., increasing the frequency when the directional velocity is towardthe user and decreasing the frequency when the directional velocity isaway from the user). The audio processing system 488 may adjust thefrequencies by applying a conventional Doppler shift algorithm.

FIG. 9C is a flow chart 940 listing the steps in an example method foradjusting amplitudes to produce audio signals corresponding to thedistance of the virtual object with respect to the head of the user. Theadjustments provide a more realistic audio experience that matches thevisual interpretation by the user.

At block 942, the system determines the distance information of thevirtual object with respect to the head of the user. The systemdetermines the distance by monitoring the current position of thevirtual object. In one example, the virtual object processing system 484periodically (e.g., every 10 ms) calculates the current position of thevirtual object (e.g., as described above with reference to block 904).The virtual object processing system 484 then calculates the distancebetween an origin associate with the head of the user and the currentposition of the virtual object.

At block 944, the system adjusts amplitudes of the left audio signal andthe right audio signal responsive to the determined distanceinformation. The processor 432 adjusts the amplitudes of the left audiosignal and the right audio signal. In an example, the audio processingsystem 488 instructs the audio processor 413 to adjust the amplitude(e.g., increasing the amplitude when the distance is relatively closeand increasing the amplitude when the distance is relatively far fromthe user). The audio processing system 488 may adjust the amplitudes byapplying a conventional linear or non-linear algorithm.

Any of the functionality described herein for the eyewear device 100,the mobile device 401, and the server system 498 can be embodied in oneor more computer software applications or sets of programminginstructions, as described herein. According to some examples,“function,” “functions,” “application,” “applications,” “instruction,”“instructions,” or “programming” are program(s) that execute functionsdefined in the programs. Various programming languages can be employedto develop one or more of the applications, structured in a variety ofmanners, such as object-oriented programming languages (e.g.,Objective-C, Java, or C++) or procedural programming languages (e.g., Cor assembly language). In a specific example, a third-party application(e.g., an application developed using the ANDROID™ or IOS™ softwaredevelopment kit (SDK) by an entity other than the vendor of theparticular platform) may include mobile software running on a mobileoperating system such as IOS™, ANDROID™, WINDOWS® Phone, or anothermobile operating systems. In this example, the third-party applicationcan invoke API calls provided by the operating system to facilitatefunctionality described herein.

Hence, a machine-readable medium may take many forms of tangible storagemedium. Non-volatile storage media include, for example, optical ormagnetic disks, such as any of the storage devices in any computerdevices or the like, such as may be used to implement the client device,media gateway, transcoder, etc. shown in the drawings. Volatile storagemedia include dynamic memory, such as main memory of such a computerplatform. Tangible transmission media include coaxial cables; copperwire and fiber optics, including the wires that comprise a bus within acomputer system. Carrier-wave transmission media may take the form ofelectric or electromagnetic signals, or acoustic or light waves such asthose generated during radio frequency (RF) and infrared (IR) datacommunications. Common forms of computer-readable media thereforeinclude for example: a floppy disk, a flexible disk, hard disk, magnetictape, any other magnetic medium, a CD-ROM, DVD or DVD-ROM, any otheroptical medium, punch cards paper tape, any other physical storagemedium with patterns of holes, a RAM, a PROM and EPROM, a FLASH-EPROM,any other memory chip or cartridge, a carrier wave transporting data orinstructions, cables or links transporting such a carrier wave, or anyother medium from which a computer may read programming code or data.Many of these forms of computer readable media may be involved incarrying one or more sequences of one or more instructions to aprocessor for execution.

Except as stated immediately above, nothing that has been stated orillustrated is intended or should be interpreted to cause a dedicationof any component, step, feature, object, benefit, advantage, orequivalent to the public, regardless of whether it is or is not recitedin the claims.

It will be understood that the terms and expressions used herein havethe ordinary meaning as is accorded to such terms and expressions withrespect to their corresponding respective areas of inquiry and studyexcept where specific meanings have otherwise been set forth herein.Relational terms such as first and second and the like may be usedsolely to distinguish one entity or action from another withoutnecessarily requiring or implying any actual such relationship or orderbetween such entities or actions. The terms “comprises,” “comprising,”“includes,” “including,” or any other variation thereof, are intended tocover a non-exclusive inclusion, such that a process, method, article,or apparatus that comprises or includes a list of elements or steps doesnot include only those elements or steps but may include other elementsor steps not expressly listed or inherent to such process, method,article, or apparatus. An element preceded by “a” or “an” does not,without further constraints, preclude the existence of additionalidentical elements in the process, method, article, or apparatus thatcomprises the element.

Unless otherwise stated, any and all measurements, values, ratings,positions, magnitudes, sizes, and other specifications that are setforth in this specification, including in the claims that follow, areapproximate, not exact. Such amounts are intended to have a reasonablerange that is consistent with the functions to which they relate andwith what is customary in the art to which they pertain. For example,unless expressly stated otherwise, a parameter value or the like mayvary by as much as plus or minus ten percent from the stated amount orrange.

In addition, in the foregoing Detailed Description, it can be seen thatvarious features are grouped together in various examples for thepurpose of streamlining the disclosure. This method of disclosure is notto be interpreted as reflecting an intention that the claimed examplesrequire more features than are expressly recited in each claim. Rather,as the following claims reflect, the subject matter to be protected liesin less than all features of any single disclosed example. Thus, thefollowing claims are hereby incorporated into the Detailed Description,with each claim standing on its own as a separately claimed subjectmatter.

While the foregoing has described what are considered to be the bestmode and other examples, it is understood that various modifications maybe made therein and that the subject matter disclosed herein may beimplemented in various forms and examples, and that they may be appliedin numerous applications, only some of which have been described herein.It is intended by the following claims to claim any and allmodifications and variations that fall within the true scope of thepresent concepts.

What is claimed is:
 1. A system for presenting audio signals to a user,the system comprising: a speaker system including a speaker forpresenting an audio signal at a location adjacent the user and anotherspeaker for presenting another audio signal at another location adjacentthe user; and a processor coupled to the speaker system, the processorconfigured to determine a current position of a virtual object withrespect to the user, the virtual object having an associated audiotrack, identify a current audio zone from a plurality of audio zonesresponsive to the determined current position, each of the plurality ofaudio zones having a corresponding predefined filter and anothercorresponding predefined filter, and apply the predefined filterscorresponding to the current audio zone to the audio track associatedwith the virtual object to produce the audio signal for presentation bythe speaker and the other audio signal for presentation by the otherspeaker, wherein each of the predefined filters for each of theplurality of audio zones is a corresponding set of digital biquadraticfilters and at least one of the corresponding sets of digitalbiquadratic filters performs between 24 and 42 calculations.
 2. Thesystem of claim 1, further comprising: a frame configured to be worn onthe user's head, the frame supporting the speaker adjacent the user'sleft ear and the other speaker adjacent the user's right ear.
 3. Thesystem of claim 2, further comprising: a left optical presentationsystem; and a right optical presentation system; wherein the processoris further configured to provide a rendering of the virtual object tothe left optical presentation system and to provide another rendering ofthe virtual object to the right optical presentation system.
 4. Thesystem of claim 1, wherein the processor is further configured todetermine a directional velocity of the virtual object with respect tothe user and adjust frequencies of the audio signal and the other audiosignal responsive to the determined directional velocity.
 5. The systemof claim 1, wherein the current position includes distance informationand wherein the processor is further configured to determine thedistance information of the virtual object with respect to the user andadjust amplitudes of the audio signal and the other audio signalresponsive to the determined distance information.
 6. The system ofclaim 1, wherein the plurality of audio zones include a number ofsectors positioned around the user and each of the number of sectorsincludes an ear level zone, an above ear level zone, and a below earlevel zone, wherein the number of sectors is 12 sectors.
 7. The systemof claim 1, wherein each of the biquadratic filters perform sixmultiply-and-accumulate operations.
 8. The system of claim 7, whereineach of the corresponding sets of digital biquadratic filters includes 4to 7 biquadratic filters.
 9. A method for presenting audio signals to auser with an audio device, the audio device having a speaker systemincluding a speaker for presenting an audio signal at a locationadjacent the user and another speaker for presenting another audiosignal at another location adjacent the user, the method comprising:determining a current position of a virtual object with respect to theuser, the virtual object having an associated audio track; identifying acurrent audio zone from a plurality of audio zones responsive to thedetermined current position, each of the plurality of audio zones havinga corresponding predefined filter and another corresponding predefinedfilter, wherein each of the predefined filters for each of the pluralityof audio zones is a corresponding set of digital biquadratic filters andeach of the corresponding sets of digital biquadratic filters performsbetween 24 and 42 calculations; and applying the predefined filterscorresponding to the current audio zone to the audio track associatedwith the virtual object to produce the audio signal for presentation bythe speaker and the other audio signal for presentation by the otherspeaker.
 10. The method of claim 9, further comprising: determining adirectional velocity of the virtual object with respect to the user; andadjusting frequencies of the audio signal and the other audio signalresponsive to the determined directional velocity.
 11. The method ofclaim 9, wherein the current position includes distance information andwherein the method further comprises: determining the distanceinformation of the virtual object with respect to the user; andadjusting amplitudes of the audio signal and the other audio signalresponsive to the determined distance information.
 12. The method ofclaim 9, wherein the plurality of audio zones include a number ofsectors positioned around the user and each of the number of sectorsincludes an ear level zone, an above ear level zone, and a below earlevel zone, wherein the number of sectors is 12 sectors.
 13. The methodof claim 9, wherein each of the biquadratic filters perform sixmultiply-and-accumulate operations.
 14. The method of claim 9, whereineach of the corresponding sets of digital biquadratic filters includes 4to 7 biquadratic filters.
 15. A non-transitory computer readable mediumincluding instructions for presenting audio signals to a user with anaudio device, the audio device having a speaker system including aspeaker for presenting an audio signal at a location adjacent the userand another speaker for presenting another audio signal at anotherlocation adjacent the user, the instructions, when performed by aprocessor, configure the processor to: determine a current position of avirtual object with respect to the user, the virtual object having anassociated audio track; identify a current audio zone from a pluralityof audio zones responsive to the determined current position, each ofthe plurality of audio zones having a corresponding predefined filterand another corresponding predefined filter, wherein each of thepredefined filters for each of the plurality of audio zones is acorresponding set of digital biquadratic filters and each of thecorresponding sets of digital biquadratic filters performs between 24and 42 calculations; and apply the predefined filters corresponding tothe current audio zone to the audio track associated with the virtualobject to produce the audio signal for presentation by the speaker andthe other audio signal for presentation by the other speaker.
 16. Thenon-transitory computer readable medium of claim 15, wherein theprocessor is further configured to provide a rendering of the virtualobject to a left optical presentation system and another rendering ofthe virtual object to a right optical presentation system.
 17. Thenon-transitory computer readable medium of claim 15, wherein theprocessor is further configured to determine a directional velocity ofthe virtual object with respect to the user and adjust frequencies ofthe audio signal and the other audio signal responsive to the determineddirectional velocity.
 18. The non-transitory computer readable medium ofclaim 15, wherein the current position includes distance information andwherein the processor is further configured to determine the distanceinformation of the virtual object with respect to the user and adjustamplitudes of the audio signal and the other audio signal responsive tothe determined distance information.
 19. The non-transitory computerreadable medium of claim 15, wherein the plurality of audio zonesinclude a number of sectors positioned around the user and each of thenumber of sectors includes an ear level zone, an above ear level zone,and a below ear level zone, wherein the number of sectors is 12 sectors.20. The non-transitory computer readable medium of claim 15, whereineach of the biquadratic filters perform six multiply-and-accumulateoperations and each of the corresponding sets of digital biquadraticfilters includes 4 to 7 biquadratic filters.